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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design of B1pF-A Large Aperture Dipole Magnet for EIC

The design of interaction region (IR) magnets for the Electron Ion Collider (EIC), demands tight boundary conditions on the magnet design given by the high field requirements and the proximity of electron and hadron beams within a common yoke and resultant crosstalk. Here, this article discusses the electromagnetic design of the superconducting collared magnet B1pF. The magnet will be built as the prototype for several collared magnets (dipoles and quadrupoles) for the hadron beam in the forward direction of the IR. The magnet design is based on a single layer coil with an inner diameter of 300 mm over a slot length of 3 m. The magnet produces an integral field of 10.34 T.m at a current of 11.9 kA to produce a nominal field of about 3.96 T at its center. Given by the common Rutherford cable parameters, the magnet will be used as a baseline for optimization of all the collared magnets. The article further discusses yoke optimizations, quench analysis, coil end design and efforts on fine tuning of field quality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Enhanced Performance of Dual Inverter with a Floating Capacitor for Motor Drive Applications

This paper studies a dual inverter supplied by a DC-link and a floating capacitor (FC), emerged as a promising inverter topology for motor drive applications. For this type of inverter, the voltage ratio between the DC-link and the FC can be actively controlled. This ratio design is crucial as it essentially defines both the DC-link voltage utilization and the inverter output quality. Several voltage ratios have previously been discussed to enhance the dual inverter performance, but only one aspect, either the voltage utilization or the output quality, is investigated. As a result, although one performance aspect can be improved, the other aspect has been adversely affected. In this work, a comparative study considering both aspects is carried out for all the possible voltage ratios. Based on this analysis, the optimal ratios for different inverter modulation indices are identified. This is followed by proposing a ratio selection strategy to double the voltage utilization without degrading the output quality. Furthermore, this strategy enables an electric drive to work at a higher maximum speed without flux weakening for a given DC-link voltage. The claimed advantages have been proved by experimental tests on an open-end windings induction motor drive.

42 ENGINEERING↗
DOE OSTI2013

Branch Flow Model: Relaxations and Convexification-Part I

We propose a branch flow model for the analysis and optimization of mesh as well as radial networks. The model leads to a new approach to solving optimal power flow (OPF) that consists of two relaxation steps. The first step eliminates the voltage and current angles and the second step approximates the resulting problem by a conic program that can be solved efficiently. For radial networks, we prove that both relaxation steps are always exact, provided there are no upper bounds on loads. For mesh networks, the conic relaxation is always exact but the angle relaxation may not be exact, and we provide a simple way to determine if a relaxed solution is globally optimal. We propose convexification of mesh networks using phase shifters so that OPF for the convexified network can always be solved efficiently for an optimal solution. We prove that convexification requires phase shifters only outside a spanning tree of the network and their placement depends only on network topology, not on power flows, generation, loads, or operating constraints. Part I introduces our branch flow model, explains the two relaxation steps, and proves the conditions for exact relaxation. Part II describes convexification of mesh networks, and presents simulation results.

Farivar, M↗
DOE OSTI2013

Branch Flow Model: Relaxations and Convexification-Part II

We propose a branch flow model for the analysis and optimization of mesh as well as radial networks. The model leads to a new approach to solving optimal power flow (OPF) that consists of two relaxation steps. The first step eliminates the voltage and current angles and the second step approximates the resulting problem by a conic program that can be solved efficiently. For radial networks, we prove that both relaxation steps are always exact, provided there are no upper bounds on loads. For mesh networks, the conic relaxation is always exact but the angle relaxation may not be exact, and we provide a simple way to determine if a relaxed solution is globally optimal. We propose convexification of mesh networks using phase shifters so that OPF for the convexified network can always be solved efficiently for an optimal solution. We prove that convexification requires phase shifters only outside a spanning tree of the network and their placement depends only on network topology, not on power flows, generation, loads, or operating constraints. Part I introduces our branch flow model, explains the two relaxation steps, and proves the conditions for exact relaxation. Part II describes convexification of mesh networks, and presents simulation results.

Farivar, M↗
DOE OSTI2023

Interoperability between Three-Phase and Single-Phase WPT Systems

This paper presents an analysis and optimal position alignments of the transmitting and receiving couplers for achieving interoperability between a three-phase and a single-phase inductive wireless power transfer (WPT) system. In addition, single-phase operation modes for the six-switch three-phase inverter are identified for maximal power transfer from the three-phase transmitter pad to the single-phase receiver pad. Simulation results are included to show the power transfer capability between a 50 kW three-phase and an 11 kW double-D or circular single-phase WPT system at various alignment positions of the couplers.

Su, Gui-Jia↗
DOE OSTI2018

PhaseChange Material Freezing in an Energy Storage Module for a Micro Environmental ControlSystem

This study analyzes phase change material (PCM) freezing process in a novel latent heat storage device (LHSD). Heat is removed from the PCM with an embedded evaporator. A mathematical model of freezing in a finite-thickness PCM slab is presented. An experimentally validated reduced-order model (ROM) based on the mathematical model was developed to analyze the heat transfer between the freezing PCM and an evaporating refrigerant flowing inside a flat, microchannel tube coil embedded in the PCM. A detailed finite element model (FEM) of the same device was also developed and employed to verify the validity of the ROM over a wider range of conditions. The freezing times and total “cooling” stored in the PCM computed by the ROM agree very well with those computed by the detailed FEM. The ROM executes in ~1 min for a full heat exchanger, compared with more than 10 h for the FEM, making the former much more practical for use in parametric analysis and optimization of design alternatives.

Engineering↗
DOE OSTI2021

Revisiting Theoretical Limits for One Degree-of-Freedom Wave Energy Converters

This work revisits the theoretical limits of one degree-of-freedom wave energy converters (WECs). This work considers the floating sphere used in the OES Task 10 WEC modeling and verification effort for analysis. Analytical equations are derived to determine bounds on displacement amplitude, time-averaged power (TAP), and power-take-off (PTO) force. A unique result found shows that the TAP absorbed by a WEC can be defined solely by the inertial properties and radiation hydrodynamic coefficients. In addition, a unique expression for the PTO force was derived that provides lower and upper bounds when resistive control is used to maximize power generation. For complex conjugate control, this same expression only provides a lower bound, as there is theoretically no upper bound. These bounds assist in comparing the performance of the floating sphere if it were to extract energy using surge or heave motion. The analysis shows because of differences in hydrodynamic coefficients for each oscillating mode, there are different frequency ranges that provide better power capture efficiency. The influence of a motion constraint on TAP while utilizing a nonideal power take-off is examined and found to reduce the losses associated with bidirectional energy flow. The expression to calculate TAP with a nonideal PTO is modified by the electrical conversion efficiency and the ratio of the PTO spring and damping coefficients. Furthermore, the PTO spring and damping coefficients were separated in the expression, allowing for limits to be set on the PTO coefficients to ensure net power generation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Calculation of Nuclear Reactor Cooling Tower Performance With Limited Data Streams

Monitoring of cooling tower performance in a nuclear reactor facility is necessary to ensure safe operation; however, instrumentation for measuring performance characteristics can be difficult to install and may malfunction or break down over long duration experiments. This paper describes employing a thermodynamic approach to quantify cooling tower performance, the Merkel model, which requires only five parameters, namely, inlet water temperature, outlet water temperature, liquid mass flowrate, gas mass flowrate, and wet bulb temperature. Using this model, a general method to determine cooling tower operation for a nuclear reactor was developed in situations when neither the outlet water temperature nor gas mass flowrate are available, the former being a critical piece of information to bound the Merkel integral. Furthermore, when multiple cooling tower cells are used in parallel (as would be in the case of large-scale cooling operations), only the average outlet temperature of the cooling system is used as feedback for fan speed control, increasing the difficulty of obtaining the outlet water temperature for each cell. To address these shortcomings, this paper describes a method to obtain individual cell outlet water temperatures for mechanical forced-air cooling towers via parametric analysis and optimization. In this method, the outlet water temperature for an individual cooling tower cell is acquired as a function of the liquid-to-gas ratio (L/G). Leveraging the tight tolerance on the average outlet water temperature, an error function is generated to describe the deviation of the parameterized L/G to the highly controlled average outlet temperature. The method was able to determine the gas flowrate at rated conditions to be within 3.9% from that obtained from the manufacturer’s specification, while the average error for the four individual cooling cell outlet water temperatures were 1.6 °C, -0.5 °C, -1.0 °C, and 0.3 °C.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Consistent Chemical Mechanism from Collaborative Data Processing

Numerical tool of Process Informatics Model (PrIMe) is mathematically rigorous and numerically efficient approach for analysis and optimization of chemical systems. It handles heterogeneous data and is scalable to a large number of parameters. The Boundto-Bound Data Collaboration module of the automated data-centric infrastructure of PrIMe was used for the systematic uncertainty and data consistency analyses of the H 2 /CO reaction model (73/17) and 94 experimental targets (ignition delay times). The empirical rule for evaluation of the shock tube experimental data is proposed. The initial results demonstrate clear benefits of the PrIMe methods for an evaluation of the kinetic data quality and data consistency and for developing predictive kinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-F-18C-01: Minimum Detectability Analysis for Comprehensive Sized Based Optimization of Image Quality and Radiation Dose Across CT Protocols

Purpose: This work involved a comprehensive modeling of task-based performance of CT across a wide range of protocols. The approach was used for optimization and consistency of dose and image quality within a large multi-vendor clinical facility. Methods: 150 adult protocols from the Duke University Medical Center were grouped into sub-protocols with similar acquisition characteristics. A size based image quality phantom (Duke Mercury Phantom) was imaged using these sub-protocols for a range of clinically relevant doses on two CT manufacturer platforms (Siemens, GE). The images were analyzed to extract task-based image quality metrics such as the Task Transfer Function (TTF), Noise Power Spectrum, and Az based on designer nodule task functions. The data were analyzed in terms of the detectability of a lesion size/contrast as a function of dose, patient size, and protocol. A graphical user interface (GUI) was developed to predict image quality and dose to achieve a minimum level of detectability. Results: Image quality trends with variations in dose, patient size, and lesion contrast/size were evaluated and calculated data behaved as predicted. The GUI proved effective to predict the Az values representing radiologist confidence for a targeted lesion, patient size, and dose. As an example, an abdomen pelvis exam for the GE scanner, with a task size/contrast of 5-mm/50-HU, and an Az of 0.9 requires a dose of 4.0, 8.9, and 16.9 mGy for patient diameters of 25, 30, and 35 cm, respectively. For a constant patient diameter of 30 cm, the minimum detected lesion size at those dose levels would be 8.4, 5, and 3.9 mm, respectively. Conclusion: The designed CT protocol optimization platform can be used to evaluate minimum detectability across dose levels and patient diameters. The method can be used to improve individual protocols as well as to improve protocol consistency across CT scanners.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-207B-04: A Preliminary Investigation of Indicators for Treatment Outcomes of CT Guided Cervical Cancer Brachytherapy

Purpose: To identify indicators for recurrence in cervical cancer patients treated with high-dose-rate brachytherapy (HDR-BT). Methods: A total of 37 biopsy proven uterine cervical cancer patients of stage IB-IVA treated between 2011 and 2015 were included in this study. All patients were treated with 37.8–52.2Gy of external beam radiotherapy (EBRT) plus 5 × 5.0–6.5Gy of HDR-BT. Patient age, standard deviation of high-risk clinical tumor volume (HR-CTVSD) collected throughout HDR-BT, and D90 (EQD2, α/β=10Gy) of the HR-CTV were investigated as potential indicators for local/distant recurrence using ROC analysis. The optimal cutoff value was identified through the Youden index and was subsequently used to obtain a group assignment for all patients. Another two comparing groups were defined per evidence of post-EBRT tumor shrinkage based on the pre-HDR MR scan. Kaplan-Meier curves were generated for recurrence-free proportions for comparing groups where time was measured from the final HDR treatment date to the date of the final follow-up exam and compared through Cox regression. Results: Patients had a median follow-up of 12 months, where 16% had local pelvic recurrence and 16% had distant recurrence. HR-CTVSD was identified as a statistically significant indicator for recurrence (AUC=0.802, p=0.007) compared to D90 (AUC=0.655, p=0.167) and patient age (AUC=0.683, p=0.103). HR-CTVSD of 6.26cc was chosen as the optimal cutoff value, which was used as the basis for patient group assignment. Patients with HR-CTVSD>6.26cc had a hazard ratio of 3.92 (95% CI-1.37, 11.24; p=0.011) for recurrence compared to HRCTVSD≤ 6.26cc. Patients without evidence of post-EBRT tumor shrinkage compared to those with had a hazard ratio of 4.28 (95% CI-1.14, 16.15; p=0.032) for recurrence. Conclusion: HR-CTVSD was identified as an indicator for recurrence and an optimal value of 6.26cc was established in our study. In addition, patients without evidence of post-EBRT tumor shrinkage demonstrated an increased recurrence rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Search for signatures of sterile neutrinos with Double Chooz

We present a search for signatures of neutrino mixing of electron anti-neutrinos with additional hypothetical sterile neutrino flavors using the Double Chooz experiment. The search is based on data from 5 years of operation of Double Chooz, including 2 years in the two-detector configuration. The analysis is based on a profile likelihood, i.e. comparing the data to the model prediction of disappearance in a data-to-data comparison of the two respective detectors. The analysis is optimized for a model of three active and one sterile neutrino. It is sensitive in the typical mass range ${5 \times 10^{-3}}\,\mathrm{eV}^2 \lesssim \varDelta m^2_{41} \lesssim {3 \times 10^{-1}}\,\mathrm{eV}^2$ for mixing angles down to $\sin ^2 2\theta _{14} \gtrsim {0.02}$. No significant disappearance additionally to the conventional disappearance related to $\theta _{13}$ is observed and correspondingly exclusion bounds on the sterile mixing parameter $\theta _{14}$ as a function of $\varDelta m^2_{41}$ are obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Python in the NERSC Exascale Science Applications Program for Data

We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codes vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices

Ronaghi, Zahra↗
DOE OSTI2018

SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

Going deeper and wider in neural architectures improves their accuracy, while the limited GPU DRAM places an undesired restriction on the network design domain. Deep Learning (DL) practitioners either need to change to less de- sired network architectures, or nontrivially dissect a network across multiGPUs. These distract DL practitioners from concentrating on their original machine learning tasks. We present SuperNeurons: a dynamic GPU memory scheduling runtime to enable the network training far beyond the GPU DRAM capacity. SuperNeurons features 3 memory optimizations, Liveness Analysis, Unified Tensor Pool, and Cost-Aware Recomputation; together they effectively reduce the network-wide peak memory usage down to the maximal memory usage among layers. We also address the performance issues in these memory-saving techniques. Given the limited GPU DRAM, SuperNeurons not only provisions the necessary memory for the training, but also dynamically allocates the memory for convolution workspaces to achieve the high performance. Evaluations against Caffe, Torch, MXNet and TensorFlow have demonstrated that SuperNeurons trains at least 3.2432 deeper network than current ones with the leading performance. Particularly, SuperNeurons can train ResNet2500 that has 104 basic network layers on a 12GB K40c.

Wang, Linnan↗
DOE OSTI2016

Kokkos GPU Compiler

The Kokkos Clang compiler is a version of the Clang C++ compiler that has been modified to perform targeted code generation for Kokkos constructs in the goal of generating highly optimized code and to provide semantic (domain) awareness throughout the compilation toolchain of these constructs such as parallel for and parallel reduce. This approach is taken to explore the possibilities of exposing the developer’s intentions to the underlying compiler infrastructure (e.g. optimization and analysis passes within the middle stages of the compiler) instead of relying solely on the restricted capabilities of C++ template metaprogramming. To date our current activities have focused on correct GPU code generation and thus we have not yet focused on improving overall performance. The compiler is implemented by recognizing specific (syntactic) Kokkos constructs in order to bypass normal template expansion mechanisms and instead use the semantic knowledge of Kokkos to directly generate code in the compiler’s intermediate representation (IR); which is then translated into an NVIDIA-centric GPU program and supporting runtime calls. In addition, by capturing and maintaining the higher-level semantics of Kokkos directly within the lower levels of the compiler has the potential for significantly improving the ability of the compiler to communicate with the developer in the terms of their original programming model/semantics.

Moss, Nicholas↗
DOE OSTI2020

HERON

HERON is a modeling toolset and plugin for RAVEN to accelerate stochastic technoeconomic assessment of the economic viability of various grid-energy system configurations, especially with application to electrical grids and integrated energy systems (IES). The frameworks enabling this toolset are INL's RAVEN and its TEAL plugin. The toolset includes automated RAVEN workflow generation tools for performing stochastic analysis and optimization driven by technoeconomic factors. The workflows generated employ RAVEN for parametric or optimizing study of grid component characteristics, and again for stochastic sampling of regulated and deregulated markets, load, and weather histories. The toolset further provides methods for economically-optimal dispatch of system components given the stochastic samples of market, load, and weather histories. The toolset allows assembling of existing and new models through the RAVEN interface to the Modelica process modeling language.

Talbot, PaulW↗
DOE OSTI2021

Hybrid Simulation Framework

HYBRID is a modeling toolset to assess the economic viability of Nuclear-Renewable Integrated Energy Systems (N-R IES). The frameworks enabling this toolset are INL’s RAVEN, its CashFlow plugin and the Modelica language. The toolset includes sample RAVEN workflows performing economic assessments. These workflows consist of: generation of stochastic time series and application of probabilistic analysis and optimization algorithms (RAVEN); a library of Modelica models representing the physical behavior of N-R IES; and the CashFlow plugin mapping physical performance to economic performance. The toolset allows assembling existing and new models such as nuclear reactors, renewable energy sources, energy storage, gas turbines, industrial processes, etc. into an N-R IES. The toolset workflows evaluate the dynamics of the N-R IES responding to stochastic conditions (electricity demand, price, etc.) and optimize the dispatch economics as well as N-R IES capacity planning.

Epiney, Aaron↗